Nursing for women's health · 2026
Sociodemographic Correlates of Longitudinal Fitbit Sleep-Data Availability Among Women in the All of Us Research Program.
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Li Xintong, Mummidi Sudhir K, Dzikowicz Dillon J, Groth Susan W, Koleck Theresa A, Maki Katherine A, Kang Jian, Dreisbach Caitlin
Аннотация
OBJECTIVES: To characterize sociodemographic and clinical factors associated with longitudinal Fitbit sleep-data availability among women and to descriptively compare Fitbit-derived sleep metrics by data-availability group and self-reported menstrual cessation status.
DESIGN: Secondary cross-sectional analysis of participant-level summaries derived from longitudinal Fitbit records.
SETTING: All of Us Research Program Registered Tier version 7 data set, using records from January 2021 through June 2022.
PARTICIPANTS: The cohort included 7,385 participants whose sex-at-birth variable was coded as female (referred to as women throughout) and who had at least one Fitbit sleep record and an overall health survey record.
METHODS: Longitudinal sleep-data availability was defined as the number of months containing at least one Fitbit sleep record and categorized as low (<7 months), medium (7 to <10 months), high (10 to <13 months), or highest (≥13 months). Multinomial logistic regression used the low-availability group as the reference.
RESULTS: The cohort was predominantly White (84.1%), non-Hispanic (94.3%), and insured (98.3%); 39.6% reported household income greater than $100,000. Overall, 1,691 participants (22.9%) were in the highest-availability group. Compared to women ages 18 to 39 years, women ages 65 to 74 years had higher adjusted odds of highest versus low availability (odds ratio [OR] = 1.31, 95% confidence interval [CI] [1.07, 1.61]). Compared to household income of $50,000 to $100,000, income greater than $100,000 was associated with higher adjusted odds of highest versus low availability (OR = 1.28, 95% CI [1.07, 1.53]). Mean device-estimated time asleep was 5.4 hr in the low-availability group and 6.2 hr in the highest-availability group. Participants reporting menstrual cessation averaged 0.3 hr (18 min) less device-estimated sleep than those not reporting cessation.
CONCLUSION: Longitudinal Fitbit sleep-data availability differed across sociodemographic groups in this bring-your-own-device cohort. These differences may affect representation, selection bias, and the generalizability of wearable-based research.
DESIGN: Secondary cross-sectional analysis of participant-level summaries derived from longitudinal Fitbit records.
SETTING: All of Us Research Program Registered Tier version 7 data set, using records from January 2021 through June 2022.
PARTICIPANTS: The cohort included 7,385 participants whose sex-at-birth variable was coded as female (referred to as women throughout) and who had at least one Fitbit sleep record and an overall health survey record.
METHODS: Longitudinal sleep-data availability was defined as the number of months containing at least one Fitbit sleep record and categorized as low (<7 months), medium (7 to <10 months), high (10 to <13 months), or highest (≥13 months). Multinomial logistic regression used the low-availability group as the reference.
RESULTS: The cohort was predominantly White (84.1%), non-Hispanic (94.3%), and insured (98.3%); 39.6% reported household income greater than $100,000. Overall, 1,691 participants (22.9%) were in the highest-availability group. Compared to women ages 18 to 39 years, women ages 65 to 74 years had higher adjusted odds of highest versus low availability (odds ratio [OR] = 1.31, 95% confidence interval [CI] [1.07, 1.61]). Compared to household income of $50,000 to $100,000, income greater than $100,000 was associated with higher adjusted odds of highest versus low availability (OR = 1.28, 95% CI [1.07, 1.53]). Mean device-estimated time asleep was 5.4 hr in the low-availability group and 6.2 hr in the highest-availability group. Participants reporting menstrual cessation averaged 0.3 hr (18 min) less device-estimated sleep than those not reporting cessation.
CONCLUSION: Longitudinal Fitbit sleep-data availability differed across sociodemographic groups in this bring-your-own-device cohort. These differences may affect representation, selection bias, and the generalizability of wearable-based research.